Automated synchronization of cardiac phases for Myocardial BOLD MRI

Introduction: Cardiac phase-resolved myocardial Blood-Oxygen-Level-Dependent (BOLD) MRI is expected to increase the diagnostic confidence for identifying the myocardial territories with reduced perfusion reserves (1). However, an accurate assessment of pathological changes in myocardial perfusion reserve using this approach requires an accurate alignment of phase-resolved images acquired at rest and under provocative stress, typically at different heart rates. Manual alignment of the rest and stress images is time consuming and can be subject to intraand/or inter-observer variability. An automated approach that can robustly and reproducibly synchronizes images acquired at rest and stress is highly desirable. One such method may be reached on the basis of the segmentation of the blood pool area in the Left Ventricle (LV) chamber to derive area curves for matching images according to their position in the curve. However, this approach is computationally intensive, susceptible to noise, and requires prior localization and segmentation of the LV. Another alternative may be to synchronize the images based on trigger times; however, while this approach can provide an estimate of the position of each image within the cardiac cycle, it does not necessarily provide the correct anatomical correspondence. The purpose of this work is to develop an automated statistical method that can reliably evaluate cardiac phase-resolved myocardial BOLD MRI through temporal synchronization of rest and stress images acquired at different heart rates, without resorting to LV segmentation algorithms.